trx_toolkit/data_msg.py: use list comprehension for bit conversion

trx_toolkit/data_msg.py: use list comprehension for bit conversion

This approach is much better than buf.append() in terms of performance.
Consider the following bit conversion benchmark code:

  usbits = [random.randint(0, 254) for i in range(GSM_BURST_LEN)]
  ubits = [int(b > 128) for b in usbits]

  for i in range(100000):
      sbits = DATAMSG.usbit2sbit(usbits)
      assert(DATAMSG.sbit2usbit(sbits) == usbits)

      sbits = DATAMSG.ubit2sbit(ubits)
      assert(DATAMSG.sbit2ubit(sbits) == ubits)

=== Before this patch:

 59603795 function calls (59603761 primitive calls) in 11.357 seconds

   Ordered by: internal time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
 59200093    3.389    0.000    3.389    0.000 {method 'append' of 'list' objects}
   100000    2.212    0.000    3.062    0.000 data_msg.py:191(usbit2sbit)
   100000    1.920    0.000    2.762    0.000 data_msg.py:214(sbit2ubit)
   100000    1.835    0.000    2.677    0.000 data_msg.py:204(sbit2usbit)
   100000    1.760    0.000    2.613    0.000 data_msg.py:224(ubit2sbit)

=== After this patch:

  803794 function calls (803760 primitive calls) in 3.547 seconds

   Ordered by: internal time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
   100000    1.284    0.000    1.284    0.000 data_msg.py:203(<listcomp>)
   100000    0.864    0.000    0.864    0.000 data_msg.py:193(<listcomp>)
   100000    0.523    0.000    0.523    0.000 data_msg.py:198(<listcomp>)
   100000    0.500    0.000    0.500    0.000 data_msg.py:208(<listcomp>)
        1    0.237    0.237    3.547    3.547 data_msg.py:25(<module>)
   100000    0.035    0.000    0.899    0.000 data_msg.py:191(usbit2sbit)
   100000    0.035    0.000    0.558    0.000 data_msg.py:196(sbit2usbit)
   100000    0.033    0.000    0.533    0.000 data_msg.py:206(ubit2sbit)
   100000    0.033    0.000    1.317    0.000 data_msg.py:201(sbit2ubit)

So the new implementation is ~70% faster in this case, and takes
significantly less function calls according to cProfile [1].

[1] https://docs.python.org/3.8/library/profile.html

Change-Id: I01c07160064c8107e5db7d913ac6dec6fc419945